Time Series Forecasting Performance of the Novel Deep Learning Algorithms on Stack Overflow Website Data

• Published in: Applied sciences Vol. 13; no. 8; p. 4781
• Main Authors: Guven, Mesut, Uysal, Fatih
• Format: Journal Article
• Language: English
• Published: Basel MDPI AG 01-04-2023
• Subjects: Accuracy; Algorithms; Analysis; Artificial intelligence; Computational linguistics; convolutional neural network; Data mining; Datasets; Deep learning; Employee motivation; Forecasting; Language processing; Learning algorithms; long short-term memory networks; Machine learning; Natural language interfaces; Neural networks; Overflow; Prices; Software development; Solar energy; Solar wind; Support vector machines; Time series; time series forecasting; trend prediction; Trends; Troubleshooting; wavenet; Web sites; Websites
• ISSN: 2076-3417; 2076-3417
• DOI: 10.3390/app13084781

Time series forecasting covers a wide range of topics, such as predicting stock prices, estimating solar wind, estimating the number of scientific papers to be published, etc. Among the machine learning models, in particular, deep learning algorithms are the most used and successful ones. This is why we only focus on deep learning models. Even though it is a hot topic, there are only a few comprehensive studies, and in many studies, there is not much detail about the tested models, which makes it impossible to constitute a comparison chart. Thus, one of the main motivations for this work is to present comprehensive research by providing details about the tested models. In this study, a corpus of the asked questions and their metadata were extracted from the software development and troubleshooting website. Then, univariate time series data were created from the frequency of the questions that included the word “python” as the tag information. In the experiments, deep learning models were trained on the extracted time series, and their prediction performances are presented. Among the tested models, the model using convolutional neural network (CNN) layers in the form of wavenet architecture achieved the best result.